Alternatives
Products that do what SeekBox does
See what 5 AIs say — side by side - plus 15 Analysis Modes
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AI that reads your page, sees it, and gives context answers.
Dec 2025
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Expert-engineered AI prompts that actually works
Jul 2026 · prompt-vault-mu-tawny.vercel.app
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Hi guys. I have been working on Hitoku Draft, an open-source, voice-first AI assistant that runs entirely locally. I posted about it already, and now it has also transcription with voice editing. Looking for feedback, as I found that outside tech circles other people still do not use this tech much. It's context-aware, in the sense that it reads your screen, documents, and active app to understand what you're working on. You can ask about PDFs, reply to emails, create calendar events, use web search, editing text, all by voice. You can download a compiled version for free with the code…
Jun 2026 · hitoku.me
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Hey folks. We built SAA (Selective Auditory Attention) after trying to find ways to make a good experience with multiple robots/multiple agents. What typically ended up happening is they'd never stop talking. This is an SDK you can put before your STT. It lets you know when your device is being spoken to or not without a wakeword. You can use it for: -Single AI, Multi human -Multi AI, Single human -Multi AI, Multi human (we recommend also adding a wakeword on top for a better system) There are two models. One that is video + audio and one that is just audio. The way it overall works is…
Jun 2026 · github.com
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Hey HN! My name is Paulo. I made this (free) web app https://www.joinoptimai.com to test, track, and iterate on AI prompts. It tests your prompts against datasets that you upload and layers that over a nice UI so you can flag AI responses & compare different prompt responses in a GitHub diff-like view. This can be used to show stakeholders how your AI response quality is iterating over time. Would love to hear your feedback. Thanks!
2024 · joinoptimai.com
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Hi HN, I'm pleased to share Promptspot, an open-source (Apache License 2.0) project that helps automate testing of large language model (LLM) prompts against an array of input data. Modern LLMs offer an enormous amount of leverage if you "teach the bot to fish" — i.e. simply prompt it with both a "system prompt" (which typically doesn't change often) and a dynamic input, which is often application state, search results, recent activity, user profile data, etc. Existing playgrounds and prompt management systems often lack the rigor and flexibility required for this dynamic approach — and as…
2023 · github.com
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